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Acceptance of online therapy for children and adolescents with digital media use disorders: perspectives from child and adolescent psychiatrists and psychotherapists in Germany.
Eur Child Adolesc Psychiatry
January 2025
German Center for Addiction Research in Childhood and Adolescence (DZSKJ), University Medical Center Hamburg-Eppendorf (UKE), Martinistrasse 52, 20246, Hamburg, Germany.
Online therapies have the potential to improve access to psychological services for individuals in need while alleviating the burden on healthcare systems. However, child and adolescent psychiatrists and psychotherapists (CAPPs) rarely integrate these services into their daily practice. This exploratory study investigates CAPPs' acceptance of online therapy, with a focus on treating children and adolescents with digital media use disorders (DMUD).
View Article and Find Full Text PDFHighly parallel simulation tool for the design of isotachophoresis experiments.
Anal Chim Acta
February 2025
Department of Mechanical Engineering, Stanford University, 488 Escondido Mall, Stanford, CA, 94305, USA. Electronic address:
Background: Isotachophoresis (ITP) is a well-established electrokinetic method for separation and preconcentration of analytes. Several simulation tools for ITP have been published, but their use for experimental design is limited by the computational time for a single run and/or by the number of conditions that can be investigated per simulation run. A large fraction of the existing solvers also do not account for ionic strength effects, which can influence whether an analyte focuses in ITP.
View Article and Find Full Text PDFPoint of view: Challenges in implementation of new immunotherapies for Alzheimer's disease.
J Prev Alzheimers Dis
January 2025
Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, BioClinicum, 171 64 Solna, Sweden; Theme Inflammation and Aging, Karolinska University Hospital, 141 86 Stockholm, Sweden.
The advancement of disease-modifying treatments (DMTs) for Alzheimer's disease (AD), along with the approval of three amyloid-targeting therapies in the US and several other countries, represents a significant development in the treatment landscape, offering new hope for addressing this once untreatable chronic progressive disease. However, significant challenges persist that could impede the successful integration of this class of drugs into clinical practice. These challenges include determining patient eligibility, appropriate use of diagnostic tools and genetic testing in patient care pathways, effective detection and monitoring of side effects, and improving the healthcare system's readiness by engaging both primary care and dementia specialists.
View Article and Find Full Text PDFImplementation of patient-reported outcome dashboards within the electronic health record to support shared decision-making in serious chronic illness.
BMJ Open Qual
January 2025
Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Background: Attending to patient-reported outcomes (PROs) using data visualisation dashboards could enhance shared decision-making (SDM) and care delivery for serious chronic illnesses. However, few studies have evaluated real-world strategies and resulting implementation outcomes of PRO dashboards.
Method: From June 2020 to January 2022, we implemented an electronic health record (EHR)-integrated PRO dashboard for advanced cancer and chronic kidney disease.
Integrated real-time intelligent control for wastewater treatment plants: Data-driven modeling for enhanced prediction and regulatory strategies.
Water Res
January 2025
State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China. Electronic address:
Both mechanical models and machine learning-based models are widely utilized for real-time dynamic control; however, their implementation in the water sector often incurs significant data and computational costs. To address these challenges, this study introduces an innovative feature extraction method designed to enhance the cost-effectiveness of dynamic control in wastewater treatment plants. The proposed method extracts dynamic features from time-series data of key substrate variables to construct a data-driven model and develop real-time control strategies.
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